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Gene Ontology

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Integration of background knowledge for automatic detection of inconsistencies in gene ontology annotation.

Bioinformatics (Oxford, England)
MOTIVATION: Biological background knowledge plays an important role in the manual quality assurance (QA) of biological database records. One such QA task is the detection of inconsistencies in literature-based Gene Ontology Annotation (GOA). This man...

Predicting protein functions using positive-unlabeled ranking with ontology-based priors.

Bioinformatics (Oxford, England)
UNLABELLED: Automated protein function prediction is a crucial and widely studied problem in bioinformatics. Computationally, protein function is a multilabel classification problem where only positive samples are defined and there is a large number ...

DeepSS2GO: protein function prediction from secondary structure.

Briefings in bioinformatics
Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets. In recent years, methods based on sequence, structure and biological networks for protein function annotation hav...

Insights into the inner workings of transformer models for protein function prediction.

Bioinformatics (Oxford, England)
MOTIVATION: We explored how explainable artificial intelligence (XAI) can help to shed light into the inner workings of neural networks for protein function prediction, by extending the widely used XAI method of integrated gradients such that latent ...

Screening of key immunerelated gene in Parkinsons disease based on WGCNA and machine learning.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study a...

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma.

Technology in cancer research & treatment
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...

Interpreting Gene Ontology Annotations Derived from Sequence Homology Methods.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project describes the functions of the gene products of organisms from all kingdoms of life in a standardized way, enabling powerful analyses of experiments involving genome-wide analysis. The scientific literature is used to c...

SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.

Bioinformatics (Oxford, England)
MOTIVATION: Medical genomics faces significant challenges in interpreting disease phenotype and genetic heterogeneity. Despite the establishment of standardized disease phenotype databases, computational methods for predicting gene-phenotype associat...

HNetGO: protein function prediction via heterogeneous network transformer.

Briefings in bioinformatics
Protein function annotation is one of the most important research topics for revealing the essence of life at molecular level in the post-genome era. Current research shows that integrating multisource data can effectively improve the performance of ...